Early recognizing of a hurricanes from public satellite images

2021 ◽  
Author(s):  
A.A. Kuzmitsky ◽  
M.I. Truphanov ◽  
O.B. Tarasova ◽  
D.V. Fedosenko
Keyword(s):  
Satellite Images ◽  
A Priori ◽  
Vortex Formation ◽  
Weather Conditions ◽  
Local Area ◽  
Weather Data ◽  
Polar Coordinate System ◽  
Practical Implementation ◽  
Characteristic Points ◽  
Moving Points

One of the key tasks associated with the fast identification of powerful tropical hurricanes, the assessment of the growth of their power, is the formation of such an input dataset, which is based on data that are technically easy and accurately recorded and calculated using existing sources located in the open accessibility. The presented work is based on the analysis of satellite images as the main data sources, and on weather data as peripheral. An obvious advantage of satellite images in comparison with other sources of data on weather conditions is their high spatial resolution, as well as the ability to obtain data from various satellites, which increases the timeliness and accuracy of retrieving primary information. The developed approach consists in performing the following main interconnected iteratively performed groups of subtasks: calculation of feature points describing the location of individual cloud areas at different points in time by using different descriptors; comparison of the same cloud areas at specified times to analyze the local directions of cloud movements; tracking of cloudiness for specified time intervals; calculation of local features for selected points of cloudiness to recognize the origin and analyze turbulence; the formation of the dynamics of changes in the local area near the trajectory of the point; recognition of primary characteristic features characterizing the transformation of local turbulences into a stable vortex formation; identification of signs of the growing of a hurricane and assessment of the primary dynamics of the increase in its power; generalization and refinement of a priori given features by analyzing similar features of known cyclones. To detect points, a modified algorithm for finding them has been introduced. To describe the points, additional descriptors are introduced based on the normalized gradient measured for the neighborhood of neighboring points and cyclically changing in the polar coordinate system. A comparative analysis of the results of applying the created method and algorithm when compared with known similar solutions revealed the following distinctive features: introduction of additional invariant orientations of features when describing characteristic points and greater stability of detecting characteristic points when analyzing cloudiness, identification of cloudiness turbulence and analysis of changes in their local characteristics and movement parameters, formation of a set of generalizing distributions when analyzing a set of moving points for the subsequent recognition of the signs of a hurricane at its initial stages of formation. The developed approach was tested experimentally in the analysis of hurricanes video recordings and their movement in the Atlantic region for the period from 2010 to 2020. The developed general approach and a specific algorithm for estimating hurricane parameters based on cloud analysis are presented. The approach is applicable for practical implementation and allows accumulating data for detecting hurricanes in real time based on publicly available data for the development of a physical and mathematical model.

scholarly journals P134 Under the weather: The Meteorological correlation in Orthopaedic Trauma and within Hertfordshire

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
M Vella-Baldacchino ◽  
J Hanrahan ◽  
S Islam ◽  
R Sofat ◽  
Martinique Vella-Baldacchino
Keyword(s):  
Weather Conditions ◽  
Local Area ◽  
Meteorological Factor ◽  
Weather Data ◽  
Neck Of Femur ◽  
Activity Data ◽  
Femur Fractures ◽  
Trauma Service ◽  
Ankle Trauma ◽  
Neck Of Femur Fracture

Abstract Background The paper aims to understand the effect of meteorological factors on the number of referrals and volume of trauma operating cases within our local area. Method Trauma data was analysed in our database: (eTrauma), a digital clinical platform that co-ordinates all admissions and: trauma theatre activity. Data consisted of number of referrals per day, patient: age, mechanism of injury and type of orthopaedic injury. Weather data was: gathered from a local weather station which: records daily weather observations. Results 1160 consultations wereanalysed, 779 required an operative intervention. Neck of femur fractures: and ankle trauma were the two most common cause of trauma, accounting for 27% and 15% respectively. Neck of femur fracture pathology were not significantly correlated with any meteorological factor studied. On the contrary, ankle trauma were the only injuries significantly correlating with temperature (p < 0.03) and due point (p < 0.04). Conclusion Weather has no effect on neck of femur fractures, the most common trauma pathology treated in our department. In all seasons allocated specific trauma lists for the latter should be arranged irrelevant of the weather conditions. We identified the days receiving highest referral rate, using this data to shape the future on call trauma service.

scholarly journals Arduino Sensor Integrated Drone for Weather Indices: A Prototype for Pre-flight Preparation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Theodore Karachalios ◽  
Dimitris Kanellopoulos ◽  
Fotis Lazarinis
Keyword(s):  
Meteorological Data ◽  
Objective Assessment ◽  
Weather Conditions ◽  
Barometric Pressure ◽  
Local Area ◽  
Weather Data ◽  
Map Reading ◽  
Micro Scale ◽  
Arduino Microcontroller ◽  
Local Weather

Commercial weather stations can effectively collect weather data for a specified area. However, their ground sensors limit the amount of data that can be logged, thus failing to collect precise meteorological data in a local area such as a micro-scale region. This happens because weather conditions at a micro-scale region can vary greatly even with small altitude changes. For now, drone operators must check the local weather conditions to ensure a safe and successful flight. This task is often a part of pre-flight preparations. Since flight conditions (and most important flight safety) are greatly affected by weather, drone operators need a more accurate localized weather map reading for the flight area. In this paper, we present the Arduino Sensor Integrated Drone (ASID) with a built-in meteorological station that logs the weather conditions in the vertical area where the drone will be deployed. ASID is an autonomous drone-based system that monitors weather conditions for pre-flight preparation. The operation of the ASID system is based on the Arduino microcontroller running automatic flight profiles to record meteorological data such as temperature, barometric pressure, humidity, etc. The Arduino microcontroller also takes photos of the horizon for an objective assessment of the visibility, the base, and the number of clouds.

Method for measuring distortions of a speech signal during its transmission over a communication channel to a biometric identification system

2020 ◽  
pp. 65-72
Author(s):  
V. V. Savchenko ◽  
A. V. Savchenko
Keyword(s):  
Speech Signal ◽  
Communication Channel ◽  
Speaker Identification ◽  
A Priori ◽  
Small Samples ◽  
Practical Implementation ◽  
Identification System ◽  
New Information ◽  
Discrimination Criterion ◽  
A Priori Uncertainty

This paper is devoted to the presence of distortions in a speech signal transmitted over a communication channel to a biometric system during voice-based remote identification. We propose to preliminary correct the frequency spectrum of the received signal based on the pre-distortion principle. Taking into account a priori uncertainty, a new information indicator of speech signal distortions and a method for measuring it in conditions of small samples of observations are proposed. An example of fast practical implementation of the method based on a parametric spectral analysis algorithm is considered. Experimental results of our approach are provided for three different versions of communication channel. It is shown that the usage of the proposed method makes it possible to transform the initially distorted speech signal into compliance on the registered voice template by using acceptable information discrimination criterion. It is demonstrated that our approach may be used in existing biometric systems and technologies of speaker identification.

scholarly journals Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3030
Author(s):  
Simon Liebermann ◽  
Jung-Sup Um ◽  
YoungSeok Hwang ◽  
Stephan Schlüter
Keyword(s):  
Neural Network ◽  
Goodness Of Fit ◽  
Renewable Energy Sources ◽  
Weather Conditions ◽  
Solar Irradiation ◽  
Weather Data ◽  
Short Term ◽  
Climate Conditions ◽  
Lstm Network ◽  
The Time Domain

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models’ performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations it shows that combining an LSTM network with a CNN yields the best performance. However, regarding the chosen GoF measures, differences to the alternative approaches are fairly small. The hybrid model’s advantage lies not in the improved GoF but in its versatility: contrary to an LSTM or a CNN, it produces good results under all tested weather conditions.

scholarly journals Advanced Flight Planning and the Benefit of In-Flight Aircraft Trajectory Optimization

2021 ◽  
Vol 13 (3) ◽  
pp. 1383
Author(s):  
Judith Rosenow ◽  
Martin Lindner ◽  
Joachim Scheiderer
Keyword(s):  
New York ◽  
Traffic Control ◽  
Traffic Management ◽  
Trajectory Optimization ◽  
Service Providers ◽  
Weather Conditions ◽  
Air Traffic ◽  
Weather Data ◽  
Weather Forecasts ◽  
Aircraft Trajectory

The implementation of Trajectory-Based Operations, invented by the Single European Sky Air Traffic Management Research program SESAR, enables airlines to fly along optimized waypoint-less trajectories and accordingly to significantly increase the sustainability of the air transport system in a business with increasing environmental awareness. However, unsteady weather conditions and uncertain weather forecasts might induce the necessity to re-optimize the trajectory during the flight. By considering a re-optimization of the trajectory during the flight they further support air traffic control towards achieving precise air traffic flow management and, in consequence, an increase in airspace and airport capacity. However, the re-optimization leads to an increase in the operator and controller’s task loads which must be balanced with the benefit of the re-optimization. From this follows that operators need a decision support under which circumstances and how often a trajectory re-optimization should be carried out. Local numerical weather service providers issue hourly weather forecasts for the coming hour. Such weather data sets covering three months were used to re-optimize a daily A320 flight from Seattle to New York every hour and to calculate the effects of this re-optimization on fuel consumption and deviation from the filed path. Therefore, a simulation-based trajectory optimization tool was used. Fuel savings between 0.5% and 7% per flight were achieved despite minor differences in wind speed between two consecutive weather forecasts in the order of 0.5 m s−1. The calculated lateral deviations from the filed path within 1 nautical mile were always very small. Thus, the method could be easily implemented in current flight operations. The developed performance indicators could help operators to evaluate the re-optimization and to initiate its activation as a new flight plan accordingly.

scholarly journals Modeling the bioconversion of polysaccharides in a continuous reactor: A case study of the production of oligogalacturonates by Dickeya dadantii

2018 ◽  
Vol 294 (5) ◽  
pp. 1753-1762 ◽  
Author(s):  
Jacques-Alexandre Sepulchre ◽  
Sylvie Reverchon ◽  
Jean-Luc Gouzé ◽  
William Nasser
Keyword(s):  
A Priori ◽  
Pectate Lyase ◽  
Degradation Process ◽  
Continuous Reactor ◽  
Practical Implementation ◽  
Dickeya Dadantii ◽  
Pectate Lyases ◽  
Upper Limit ◽  
Promising Avenue

In the quest for a sustainable economy of the Earth's resources and for renewable sources of energy, a promising avenue is to exploit the vast quantity of polysaccharide molecules contained in green wastes. To that end, the decomposition of pectin appears to be an interesting target because this polymeric carbohydrate is abundant in many fruit pulps and soft vegetables. To quantitatively study this degradation process, here we designed a bioreactor that is continuously fed with de-esterified pectin (PGA). Thanks to the pectate lyases produced by bacteria cultivated in the vessel, the PGA is depolymerized into oligogalacturonates (UGA), which are continuously extracted from the tank. A mathematical model of our system predicted that the conversion efficiency of PGA into UGA increases in a range of coefficients of dilution until reaching an upper limit where the fraction of UGA that is extracted from the bioreactor is maximized. Results from experiments with a continuous reactor hosting a strain of the plant pathogenic bacterium Dickeya dadantii and in which the dilution coefficients were varied quantitatively validated the predictions of our model. A further theoretical analysis of the system enabled an a priori comparison of the efficiency of eight other pectate lyase–producing microorganisms with that of D. dadantii. Our findings suggest that D. dadantii is the most efficient microorganism and therefore the best candidate for a practical implementation of our scheme for the bioproduction of UGA from PGA.

scholarly journals THE WAYS OF TECHNICAL REALIZATION OF ADAPTIVE ALGORITHM OF COMPENSATION OF NON-LINEAR DISTORTIONS OF RADIO DEVICES

2018 ◽  
Vol 6 (52) ◽  
pp. 140-143
Author(s):  
О. Shefer ◽  
N. Ichanska ◽  
B. Topikha ◽  
V. Shefer
Keyword(s):  
Adaptive Systems ◽  
Adaptive Filters ◽  
A Priori ◽  
Weather Conditions ◽  
Adaptive Method ◽  
Theory And Practice ◽  
Modern Theory ◽  
Additional Advantage ◽  
Local Systems ◽  
Non Linear

The practical realization of potential opportunities of onboard radio local systems of radio local systems (OBRLS) that are currently considerably higher than their real approachable technical characteristics is one of the main tasks of modern theory and practice of electronic and telecommunication. The authors of the article proposed some specific technical offers and ways of physical realization of scientifically grounded algorithm of adaptive compensation of non linear distortions (ACNLD). The insertion of artificial main and supportive entrances into the scheme of non-linear adaptive compensators allowed using the general theory of adaptive systems for their synthesis. The practical usage of synthesized following such a principle ACNLD according to the created recommendations allows to significantly increase the indices of quality of OBRLS in the real conditions of their functioning, comparing with the already known ones. An additional advantage of proposed adaptive method of expansion of linear dynamic diapason (LDD) is an improvement of all-weather of OBRLS and increasing of probability of identification of radio local maps of locality captured in different weather conditions without any additional changeovers. Except for this, a flexible reserve for the noise immunity of OBRLS is being fulfilled that allows taking into consideration the possible improvements of means of radio electronic struggle. Synthesized ACNLD are considerably free from many drawbacks of linear determined means of expansion of dynamic diapason of radio receiving devices (RRD) and also they have simpler apparatus realization. Except, in a process of projection of ACNLD a considerably less volume of a priori information about the parameters of LDD is needed for the calculation of already known schemes of depression of non-linear distortions. The transferring functions of adaptive filters of ACNLD are quite quickly gather at the non-linear transferring function of radio device (RD) provided that an effective convergence can be seen only with the presence of the inner noises at least unless they exceed the non-linear distortions by the level.

scholarly journals Review of Weather Forecast Services for Ship Routing Purposes

2019 ◽  
Vol 26 (4) ◽  
pp. 80-89
Author(s):  
Marcin Życzkowski ◽  
Joanna Szłapczyńska ◽  
Rafał Szłapczyński
Keyword(s):  
Collision Avoidance ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Weather Data ◽  
Ocean Engineering ◽  
Ship Routing ◽  
Engineering Research ◽  
Fishing Vessels ◽  
Analysis Of Stability

Abstract Weather data is nowadays used in a variety of navigational and ocean engineering research problems: from the obvious ones like voyage planning and routing of sea-going vessels, through the analysis of stability-related phenomena, to detailed modelling of ships’ manoeuvrability for collision avoidance purposes. Apart from that, weather forecasts are essential for passenger cruises and fishing vessels that want to avoid the risk associated with severe hydro-meteorological conditions. Currently, there is a wide array of services that offer weather predictions. These services include the original sources – services that make use of their own infrastructure and research models – as well as those that further postprocess the data obtained from the original sources. The existing services also differ in their update frequency, area coverage, geographical resolution, natural phenomena taken into account and finally – output file formats. In the course of the ROUTING project, primarily addressing ship weather routing accounting for changeable weather conditions, the necessity arose to prepare a report on the state-of-the-art in numerical weather prediction (NWP) modelling. Based on the report, this paper offers a thorough review of the existing weather services and detailed information on how to access the data offered by these services. While this review has been done with transoceanic ship routing in mind, hopefully it will also be useful for a number of other applications, including the already mentioned collision avoidance solutions.

scholarly journals An IoT based Low-cost Weather Monitoring System for Smart Farming

2021 ◽  
Author(s):  
L.P.S.S.K. Dayananda ◽  
A. Narmilan ◽  
P. Pirapuraj
Keyword(s):  
Liquid Crystal ◽  
Mobile Phone ◽  
Real Time ◽  
Monitoring System ◽  
Liquid Crystal Display ◽  
Low Cost ◽  
Weather Conditions ◽  
Weather Data ◽  
The Internet ◽  
Arduino Uno

Background: Weather monitoring is an important aspect of crop cultivation for reducing economic loss while increasing productivity. Weather is the combination of current meteorological components, such as temperature, wind direction and speed, amount and kind of precipitation, sunshine hours and so on. The weather defines a time span ranging from a few hours to several days. The periodic or continuous surveillance or the analysis of the status of the atmosphere and the climate, including parameters such as temperature, moisture, wind velocity and barometric pressure, is known as weather monitoring. Because of the increased usage of the internet, weather monitoring has been upgraded to smart weather monitoring. The Internet of Things (IoT) is one of the new technology that can help with many precision farming operations. Smart weather monitoring is one of the precision agriculture technologies that use sensors to monitor correct weather. The main objective of the research is to design a smart weather monitoring and real-time alert system to overcome the issue of monitoring weather conditions in agricultural farms in order for farmers to make better decisions. Methods: Different sensors were used in this study to detect temperature and humidity, pressure, rain, light intensity, CO2 level, wind speed and direction in an agricultural farm and real time clock sensor was used to measured real time weather data. The major component of this system was an Arduino Uno microcontroller and the system ran according to a program written in the Arduino Uno software. Result: This is a low-cost smart weather monitoring system. This system’s output unit were a liquid crystal display and a GSM900A module. The weather data was displayed on a liquid crystal display and the GSM900A module was used to send the data to a mobile phone. This smart weather station was used to monitor real-time weather conditions while sending weather information to the farmer’s mobile phone, allowing him to make better decisions to increase yield.

scholarly journals Empirical evidence reveals the phase diagram of patch patterns in Mediterranean drylands

2017 ◽  
Author(s):  
Fernando Meloni ◽  
Cristiano R. F. Granzotti ◽  
Alexandre S. Martinez
Keyword(s):  
Phase Diagram ◽  
Phase Transitions ◽  
Satellite Images ◽  
A Priori ◽  
Continuous Phase ◽  
Adequate Description ◽  
Scaling Exponents ◽  
Open Issue ◽  
The Subject ◽  
Ecological Functioning

AbstractDrylands are ecosystems with limited water resources, often subjected to desertification. Conservation and restoration efforts towards these ecosystems depend on the interplay between ecological functioning and spatial patterns formed by local vegetation. Despite recent advances on the subject, an adequate description of phase transitions between the various vegetated phases remains an open issue. Here, we gather vegetation data of drylands from Southern Spain using satellite images. Our findings support three vegetated phases, separated by two distinct phase transitions, including a continuous phase transition, with new relations between scaling exponents of ecological variables. The phase diagram is obtained without a priori assumption about underlying ecological dynamics. We apply our analysis to a different dryland system in the Western United States and verify a compatible critical behavior, in agreement with the universality hypothesis.

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